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Open AccessArticle

A Framework for Automated Acquisition and Processing of As-Built Data with Autonomous Unmanned Aerial Vehicles

Chair of Computing in Engineering, Ruhr-Universität Bochum, 44787 Bochum, Germany
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This paper is an expanded version of Freimuth, H.; König, M. A Toolchain for Automated Acquisition and Processing of As-Built Data with Autonomous UAVs. In Proceedings of the 2019 European Conference on Computing in Construction, Chania, Greece, 10–12 July 2019.
Sensors 2019, 19(20), 4513; https://doi.org/10.3390/s19204513
Received: 27 August 2019 / Revised: 4 October 2019 / Accepted: 11 October 2019 / Published: 17 October 2019
Planning and scheduling in construction heavily depend on current information about the state of construction processes. However, the acquisition process for visual data requires human personnel to take photographs of construction objects. We propose using unmanned aerial vehicle (UAVs) for automated creation of images and point cloud data of particular construction objects. The method extracts locations of objects that require inspection from Four Dimensional Building Information Modelling (4D-BIM). With this information at hand viable flight missions around the known structures of the construction site are computed. During flight, the UAV uses stereo cameras to detect and avoid any obstacles that are not known to the model, for example moving humans or machinery. The combination of pre-computed waypoint missions and reactive avoidance ensures deterministic routing from takeoff to landing and operational safety for humans and machines. During flight, an additional software component compares the captured point cloud data with the model data, enabling automatic per-object completion checking or reconstruction. The prototype is developed in the Robot Operating System (ROS) and evaluated in Software-In-The-Loop (SITL) simulations for the sake of being executable on real UAVs. View Full-Text
Keywords: as-built; data acquisition; BIM; UAV; point cloud; octree; ROS; depth camera; obstacle avoidance as-built; data acquisition; BIM; UAV; point cloud; octree; ROS; depth camera; obstacle avoidance
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Freimuth, H.; König, M. A Framework for Automated Acquisition and Processing of As-Built Data with Autonomous Unmanned Aerial Vehicles. Sensors 2019, 19, 4513.

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